Securing data presented during videoconferencing

ABSTRACT

A method includes: determining, by a videoconference server, a level of tolerated risk for a videoconference between a presenter and an attendee; obtaining, by the videoconference server, sensor data from at least one sensor at a location where a user device of the attendee displays the videoconference; generating, by the videoconference server, a current risk score based on the sensor data; determining, by the videoconference server, the current risk score exceeds the level of tolerated risk; and presenting, by the videoconference server and in response to the determining the current risk score exceeds the level of tolerated risk, an alert to the presenter of the videoconference.

BACKGROUND

Aspects of the present invention relate generally to videoconferencingand, more particularly, to securing data presented duringvideoconferencing.

One type of electronic meeting is videoconferencing, which is theholding of a conference among people at remote locations by way oftransmitted audio and video signals. Videoconferencing typicallyinvolves each user being connected to a videoconferencing server viatheir computing device. Video of the videoconference is displayed byeach user's computing device, e.g., in an interface of thevideoconference program. Audio of the videoconference is output byspeakers included in or connected to each user's computing device. Insome instances, a user computing device may include a camera forcapturing video of the user and a microphone for capturing audio of theuser, which is combined into the stream of the videoconference that isseen and heard by other users.

A common feature of videoconferencing is to share one's screen withother members of the videoconference. Using this feature, a user mayshow a document displayed in a window on their computing device to otherusers in the videoconference. The screenshare appears in the otherusers' videoconference interface.

SUMMARY

In a first aspect of the invention, there is a computer-implementedmethod including: determining, by a videoconference server, a level oftolerated risk for a videoconference between a presenter and anattendee; obtaining, by the videoconference server, sensor data from atleast one sensor at a location where a user device of the attendeedisplays the videoconference; generating, by the videoconference server,a current risk score based on the sensor data; determining, by thevideoconference server, the current risk score exceeds the level oftolerated risk; and presenting, by the videoconference server and inresponse to the determining the current risk score exceeds the level oftolerated risk, an alert to the presenter of the videoconference.

In another aspect of the invention, there is a computer program productincluding one or more computer readable storage media having programinstructions collectively stored on the one or more computer readablestorage media. The program instructions are executable to cause avideoconference server to: determine a level of tolerated risk for avideoconference between a presenter and an attendee; obtain sensor datafrom at least one sensor at a location where a user device of theattendee displays the videoconference; generate a current risk scorebased on the sensor data, wherein the current risk score is aprobability that another person is in the location where the user deviceof the attendee displays the videoconference; determine the current riskscore exceeds the level of tolerated risk; and in response to thedetermining the current risk score exceeds the level of tolerated risk,present an alert to the presenter of the videoconference.

In another aspect of the invention, there is system including aprocessor, a computer readable memory, one or more computer readablestorage media, and program instructions collectively stored on the oneor more computer readable storage media. The program instructions areexecutable to: determine a level of tolerated risk for a videoconferencebetween a presenter and an attendee; obtain sensor data from at leastone sensor at a location where a user device of the attendee displaysthe videoconference; generate a current risk score based on the sensordata, wherein the current risk score is a probability that anotherperson is in the location where the user device of the attendee displaysthe videoconference; determine the current risk score exceeds the levelof tolerated risk; and in response to the determining the current riskscore exceeds the level of tolerated risk concurrently with confidentialdata being displayed in the videoconference, present an alert to thepresenter of the videoconference

BRIEF DESCRIPTION OF THE DRAWINGS

Aspects of the present invention are described in the detaileddescription which follows, in reference to the noted plurality ofdrawings by way of non-limiting examples of exemplary embodiments of thepresent invention.

FIG. 1 depicts a cloud computing node according to an embodiment of thepresent invention.

FIG. 2 depicts a cloud computing environment according to an embodimentof the present invention.

FIG. 3 depicts abstraction model layers according to an embodiment ofthe present invention.

FIG. 4 shows a block diagram of an exemplary environment in accordancewith aspects of the invention.

FIG. 5 shows an exemplary use case in accordance with aspects of theinvention.

FIG. 6 shows a flowchart of an exemplary method in accordance withaspects of the invention.

FIG. 7 shows a flowchart of an exemplary method in accordance withaspects of the invention.

DETAILED DESCRIPTION

Aspects of the present invention relate generally to videoconferencingand, more particularly, to securing data presented duringvideoconferencing. Implementations of the invention leverage sensor dataand artificial intelligence (AI) to detect when confidential datapresented during a videoconference is susceptible to being viewed by anunauthorized person. In response to this detecting, embodiments causethe videoconference system to output an alert to one or both of thevideoconference presenter and the videoconference attendee. In thismanner, implementations of the invention are usable to provide securitymeasures for confidential data that is displayed during avideoconference.

Organizations constantly struggle to secure their critical data withintheir own premises, as well as outside their premises, for multiplesecurity compliance reasons. A data security breach could happen eitherbecause of human error or with malicious intent.

An organization's endpoint devices such as laptops, mobile tablets,smartphones, and handheld gadgets are the new way of working due to easeof mobility and accessibility; however, managing the security of thesedevices is difficult. Users often utilize these devices to access theorganization's data by connecting to unsecured networks such as publicnetworks and private networks that are outside the control of theorganization. This behavior increases the likelihood of a data breachbecause of the unsecure network connections.

To reduce the likelihood of a data breach, organizations sometimesprovide their users with secure data communication through a virtualprivate network (VPN) using a firewall with which data is encrypted whenat rest and in motion. There are also solutions available that providesecure cloud or on-premises storage of backups of data saved on endpointdevices. Using these solutions, a user that loses their endpoint devicecan have their data restored from the backup.

Another security level for endpoint devices is achieved using securitymonitoring and analysis, which captures data on the overall state of asystem, including endpoint devices and connectivity traffic. This datais analyzed to detect possible security violations or potential systemthreats based on anomalous behavior.

Multi-factor authentication is yet another way of securing data accesson endpoint devices. But it is still critical to ensure that endpointsdevices are secured from possible data breach, tampering, andmanipulation, which could result in financial loss to an organization.

Videoconferencing is near-ubiquitous and has become a normal way tocommunicate in both personal and professional settings. In theprofessional setting, videoconferencing is a normal way to communicatewith co-workers and other collaborators. In some situations,confidential data is shared during the videoconference. For example, auser may screenshare a document during the videoconference, and thedocument being shared may include confidential data that is intended tobe seen only by the attendees of the videoconference. However, there aresituations when a person that is not an attendee of the videoconferencecan visually see the display of the videoconference as it is displayedby the device of an attendee. For example, a videoconference attendeemay be seated and participating in a videoconference using their laptop,and a non-attendee may walk near where the attendee is seated and beable to see the display of the laptop. In this situation, thenon-attendee is able to see the visual content of the videoconference,which might include confidential data that the non-attendee is notauthorized to see. This is a form of data breach that is present iscurrent videoconferencing systems.

Implementations of the invention address these problems by providingenhancements to videoconferencing systems that detect when anunauthorized person is capable of seeing confidential data presentedduring a videoconference and, in response to the detecting, cause thevideoconference system to output an alert to one or both of thevideoconference presenter and the videoconference attendee. Inembodiments, the system detects and connects with Internet of Things(IoT) sensors or security devices at the attendee's location andutilizes the output of these sensors or security devices to predict whenanother person is in a position to see the attendee's computer displaythat is displaying content of the videoconference. In embodiments, thesystem includes an artificial intelligence component, such as one ormore machine learning models, that receive the sensor data as input andthat output a scored probability that another user can see thevideoconference on the attendee's device. In this manner,implementations of the invention address the above-described problem ofdata breach during videoconferencing by collecting specialized sensordata, using the sensor data with artificial intelligence to predict ascored probability of a data breach, and generating an alert when thescored probability exceeds a threshold.

As will be understood from the description herein, implementations ofthe invention may include a computer implemented method comprising:identifying, by a computer, a Level of Tolerated Risk (LTR) associatedwith presentation content; determining, by the computer, using an AImodel, that a present level of risk associated with a presentationenvironment exceeds the LTR; and initiating, by the computer, aCautionary Action (CA) in response to the determining. The LTR may bebased on the attributes of the presentation material (e.g., extractedfrom content metadata or provided by a content provider). The AI modelmay be trained to recognize conditions relevant to the presentationenvironment (e.g., as indicated by IoT sensors associated with thepresentation environment). The AI model may consider presentationenvironment conditions indicated by recognized facial expressions of arelevant presenter. The CA may provide a warning to a presenterregarding the presence in the presentation environment of at least oneof an unwanted audience member, an unwanted recording device, andunwanted presentation recording software. The CA may provide a visualindication to the presenter (e.g., a color-coded screen overlay, etc.).The computer may be in communication with the IoT sensors locatedproximate to the presentation environment.

As described herein, a videoconference presenter may presentconfidential data to the videoconference attendees, and this data may beat risk of a breach due to other persons being able to see theattendees' display of the videoconference. Implementations of theinvention improve a presenter's experience in the video conference byproviding security measures to help reduce the likelihood of such abreach. Implementations may be used in addition to existing multi-factorauthentication mechanisms by which an attendee confirms their identifybefore joining the videoconference.

Embodiments provide a mechanism that will detect if a third-party personis in the attendee's endpoint device field of view. Implementations mayuse one or more different types of sensors to detect a third-partyperson within the vicinity of the attendee's endpoint device.

Implementations can be used to enhance videoconference software todetect existing IoT sensors or security devices in the vicinity of anattendee's endpoint device. Examples of such sensors include but are notlimited to cameras, ultrasonic sensors, infrared sensors, lightdetection and ranging (LIDAR) sensors, Li-Fi sensors, microphones, andcarbon content detection sensors. In embodiments, when an attendeeendpoint device is first connecting to a videoconference, a systemcauses the attendee endpoint device to discover and connect to suchsensors that are within a same room as the attendee endpoint device. Inembodiments, the system leverages the output of the connected sensors todetect when another person enters the room with the attendee during thevideoconference, and to generate an alert to the attendee and/or thevideoconference presenter based on the detecting the other person hasentered the room.

Implementations may be used to enhance videoconferencing systems byconfiguring the systems to learn and recognize user expressions that areassociated with another person entering a room with an attendee of thevideoconference. This may be performed using an AI component such as amachine learning model that is trained to recognize user expressionsthat are associated with another person entering a room. In this manner,the system may use the machine learning model in real time during avideoconference to detect when a person has entered a room with anattendee of the videoconference. In one example, the user expressionscomprise facial expressions and the AI component comprises aconvolutional neural network (CNN) trained for facial expressionrecognition.

Implementations may be used to prevent a third-party person fromobtaining an image of the attendee's endpoint device while the endpointdevice is displaying confidential data during the videoconference. Inembodiments, this is achieved using infrared blocking techniques.

In embodiments, the system determines a subset of IoT sensors to use fordetecting the presence of an unauthorized person in the room with thevideoconference attendee. In these embodiments, the system may enablecommunication with the determined subset of IoT sensors and disablecommunication with other ones of the IoT sensors that are not includedin the subset.

In implementations, the system generates an alert to the videoconferencepresenter when a determined risk score exceeds a predefined threshold.The alert can be in the form of a hint that is presented to thevideoconference presenter in their interface of the videoconference. Inresponse to receiving the hint, the videoconference presenter may takeaction to stop displaying the confidential material in thevideoconference. In one example, the videoconference presenter may stopa screen share of a confidential document. In another example, thevideoconference presenter may disconnect the attendee from thevideoconference. In one exemplary implementation, the hint comprises oneof plural different visualizations that signify different levels ofconcern, such as a green icon signifying a low level of concern of adata breach, a yellow icon signifying a medium level of concern, and ared icon signifying a high level of concern.

Implementations as described herein enable a videoconferencing system toidentify a confidentiality level requirement for a videoconference asset by the presenter. The confidentiality level requirement may be oneof high, medium, and low, for example. The confidentiality levelrequirement may be identified using machine learning techniques thatdetermine the confidentiality from the content of the videoconferencebefore presentation in the videoconference. The confidentiality levelrequirement may be identified using a tagging method in which a frame inthe video or slide in the presentation is tagged as confidential.

Implementations as described herein enable a videoconferencing system toprovide a presenter with a view through which the presenter can setrequired preferences before starting or setting up the videoconference.In this way, the videoconference attendees are made aware of andunderstand prerequisites for attending the videoconference. Theprerequisites may include for example: each attendee should be alone inthe field of view of their camera while confidential data is displayed;attendees should not screenshot an interface of the videoconference onthe attendee's endpoint device; and attendees should not save content ofthe videoconference on the attendee's endpoint device using backgroundrecording software.

Implementations as described herein enable a videoconferencing system todetect and connect to existing IoT sensors in an attendee's location(e.g., room) using application programming interfaces (APIs) of the IoTsensors. In embodiments, the system creates categories of sensors basedon the output data streams the sensors provide. In embodiments, thesystem processes data steams coming from the IoT sensors, such as amotion detector in the room, a sound detector trained for humanidentification, ultrasonic sensors, carbon content-based detectors, andLi-Fi based detectors that can identify human presence in the same roomas the attendee endpoint device.

Implementations as described herein enhance a videoconferencing systemby helping an attendee's endpoint device connect with IoT sensorsautomatically when the videoconference begins. In embodiments, theendpoint device is configured to identify to the videoconferencingsystem whether the endpoint device has ultrasonic and/or infraredsensors installed in the endpoint device itself, and to enable thevideoconferencing system to use these sensors during thevideoconference. In embodiments, the endpoint device is configured toidentify to the videoconferencing system whether the endpoint device hassome form of background recording and/or screenshot capabilityinstalled, and to enable the videoconferencing system to disable thesefunctions on the endpoint device during the videoconference. In thismanner, implementations as described herein enable a videoconferencingsystem to collaborate with existing hardware sensors and softwarecapability on the attendee's endpoint device, and to collect informationfrom these sensors and software for the purpose of maintaining theconfidentiality of data presented in the videoconference.

Implementations as described herein enable a videoconferencing system tocheck whether the attendee's endpoint device has permission to accessthe IoT sensors in the room, to enable or disable the connection tocertain ones of the IoT sensors during the videoconference, and tocollect data from the IoT sensors for analysis. In embodiments, thesystem uses a machine learning model to learn facial expressions of theattendee that indicate another person is on the room. In this manner,the system may use the trained machine learning model in real time, withthe attendee's facial expressions during the videoconference, to predictwhether another person is in the room with the attendee.

Implementations as described herein enable a videoconferencing system todetect which IoT sensor data is relevant for identifying anomalies basedon the defined confidentiality of the videoconference and analysis ofthe IoT sensor data. In embodiments and based on this relevancydetermination, the system may selectively enable or disable an IoTsensor data stream during the videoconference.

Implementations as described herein enable a videoconferencing system toprovide a hint to the videoconference presenter when an anomaly isdetected during the videoconference. In response, the videoconferencepresenter can communicate with the attendee to indicate that theattendee's endpoint device does not meet the confidentiality criteriafor attending the videoconference.

Implementations as described herein enable a videoconferencing system tocapture environment anomalies and change a color of a visual indicatordisplayed in the videoconference based on a level of security. In thismanner, by using a visual indicator, the presenter may be notified ofthe anomaly even if their audio is on mute.

It should be understood that, to the extent implementations of theinvention collect, store, or employ personal information provided by, orobtained from, individuals, such information shall be used in accordancewith all applicable laws concerning protection of personal information.Additionally, the collection, storage, and use of such information maybe subject to consent of the individual to such activity, for example,through “opt-in” or “opt-out” processes as may be appropriate for thesituation and type of information. Storage and use of personalinformation may be in an appropriately secure manner reflective of thetype of information, for example, through various encryption andanonymization techniques for particularly sensitive information.

The present invention may be a system, a method, and/or a computerprogram product at any possible technical detail level of integration.The computer program product may include a computer readable storagemedium (or media) having computer readable program instructions thereonfor causing a processor to carry out aspects of the present invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium or media, as used herein, is not to beconstrued as being transitory signals per se, such as radio waves orother freely propagating electromagnetic waves, electromagnetic wavespropagating through a waveguide or other transmission media (e.g., lightpulses passing through a fiber-optic cable), or electrical signalstransmitted through a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, configuration data for integrated circuitry, oreither source code or object code written in any combination of one ormore programming languages, including an object oriented programminglanguage such as Smalltalk, C++, or the like, and procedural programminglanguages, such as the “C” programming language or similar programminglanguages. The computer readable program instructions may executeentirely on the user's computer, partly on the user's computer, as astand-alone software package, partly on the user's computer and partlyon a remote computer or entirely on the remote computer or server. Inthe latter scenario, the remote computer may be connected to the user'scomputer through any type of network, including a local area network(LAN) or a wide area network (WAN), or the connection may be made to anexternal computer (for example, through the Internet using an InternetService Provider). In some embodiments, electronic circuitry including,for example, programmable logic circuitry, field-programmable gatearrays (FPGA), or programmable logic arrays (PLA) may execute thecomputer readable program instructions by utilizing state information ofthe computer readable program instructions to personalize the electroniccircuitry, in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a computer, or other programmable data processing apparatusto produce a machine, such that the instructions, which execute via theprocessor of the computer or other programmable data processingapparatus, create means for implementing the functions/acts specified inthe flowchart and/or block diagram block or blocks. These computerreadable program instructions may also be stored in a computer readablestorage medium that can direct a computer, a programmable dataprocessing apparatus, and/or other devices to function in a particularmanner, such that the computer readable storage medium havinginstructions stored therein comprises an article of manufactureincluding instructions which implement aspects of the function/actspecified in the flowchart and/or block diagram block or blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the blocks may occur out of theorder noted in the Figures. For example, two blocks shown in successionmay, in fact, be accomplished as one step, executed concurrently,substantially concurrently, in a partially or wholly temporallyoverlapping manner, or the blocks may sometimes be executed in thereverse order, depending upon the functionality involved. It will alsobe noted that each block of the block diagrams and/or flowchartillustration, and combinations of blocks in the block diagrams and/orflowchart illustration, can be implemented by special purposehardware-based systems that perform the specified functions or acts orcarry out combinations of special purpose hardware and computerinstructions.

It is to be understood that although this disclosure includes a detaileddescription on cloud computing, implementation of the teachings recitedherein are not limited to a cloud computing environment. Rather,embodiments of the present invention are capable of being implemented inconjunction with any other type of computing environment now known orlater developed.

Cloud computing is a model of service delivery for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g., networks, network bandwidth, servers, processing,memory, storage, applications, virtual machines, and services) that canbe rapidly provisioned and released with minimal management effort orinteraction with a provider of the service. This cloud model may includeat least five characteristics, at least three service models, and atleast four deployment models.

Characteristics are as follows:

On-demand self-service: a cloud consumer can unilaterally provisioncomputing capabilities, such as server time and network storage, asneeded automatically without requiring human interaction with theservice's provider.

Broad network access: capabilities are available over a network andaccessed through standard mechanisms that promote use by heterogeneousthin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to servemultiple consumers using a multi-tenant model, with different physicaland virtual resources dynamically assigned and reassigned according todemand. There is a sense of location independence in that the consumergenerally has no control or knowledge over the exact location of theprovided resources but may be able to specify location at a higher levelof abstraction (e.g., country, state, or datacenter).

Rapid elasticity: capabilities can be rapidly and elasticallyprovisioned, in some cases automatically, to quickly scale out andrapidly released to quickly scale in. To the consumer, the capabilitiesavailable for provisioning often appear to be unlimited and can bepurchased in any quantity at any time.

Measured service: cloud systems automatically control and optimizeresource use by leveraging a metering capability at some level ofabstraction appropriate to the type of service (e.g., storage,processing, bandwidth, and active user accounts). Resource usage can bemonitored, controlled, and reported providing transparency for both theprovider and consumer of the utilized service.

Service Models are as follows:

Software as a Service (SaaS): the capability provided to the consumer isto use the provider's applications running on a cloud infrastructure.The applications are accessible from various client devices through athin client interface such as a web browser (e.g., web-based e-mail).The consumer does not manage or control the underlying cloudinfrastructure including network, servers, operating systems, storage,or even individual application capabilities, with the possible exceptionof limited user-specific application configuration settings.

Platform as a Service (PaaS): the capability provided to the consumer isto deploy onto the cloud infrastructure consumer-created or acquiredapplications created using programming languages and tools supported bythe provider. The consumer does not manage or control the underlyingcloud infrastructure including networks, servers, operating systems, orstorage, but has control over the deployed applications and possiblyapplication hosting environment configurations.

Infrastructure as a Service (IaaS): the capability provided to theconsumer is to provision processing, storage, networks, and otherfundamental computing resources where the consumer is able to deploy andrun arbitrary software, which can include operating systems andapplications. The consumer does not manage or control the underlyingcloud infrastructure but has control over operating systems, storage,deployed applications, and possibly limited control of select networkingcomponents (e.g., host firewalls).

Deployment Models are as follows:

Private cloud: the cloud infrastructure is operated solely for anorganization. It may be managed by the organization or a third party andmay exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by severalorganizations and supports a specific community that has shared concerns(e.g., mission, security requirements, policy, and complianceconsiderations). It may be managed by the organizations or a third partyand may exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the generalpublic or a large industry group and is owned by an organization sellingcloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or moreclouds (private, community, or public) that remain unique entities butare bound together by standardized or proprietary technology thatenables data and application portability (e.g., cloud bursting forload-balancing between clouds).

A cloud computing environment is service oriented with a focus onstatelessness, low coupling, modularity, and semantic interoperability.At the heart of cloud computing is an infrastructure that includes anetwork of interconnected nodes.

Referring now to FIG. 1 , a schematic of an example of a cloud computingnode is shown. Cloud computing node 10 is only one example of a suitablecloud computing node and is not intended to suggest any limitation as tothe scope of use or functionality of embodiments of the inventiondescribed herein. Regardless, cloud computing node 10 is capable ofbeing implemented and/or performing any of the functionality set forthhereinabove.

In cloud computing node 10 there is a computer system/server 12, whichis operational with numerous other general purpose or special purposecomputing system environments or configurations. Examples of well-knowncomputing systems, environments, and/or configurations that may besuitable for use with computer system/server 12 include, but are notlimited to, personal computer systems, server computer systems, thinclients, thick clients, hand-held or laptop devices, multiprocessorsystems, microprocessor-based systems, set top boxes, programmableconsumer electronics, network PCs, minicomputer systems, mainframecomputer systems, and distributed cloud computing environments thatinclude any of the above systems or devices, and the like.

Computer system/server 12 may be described in the general context ofcomputer system executable instructions, such as program modules, beingexecuted by a computer system. Generally, program modules may includeroutines, programs, objects, components, logic, data structures, and soon that perform particular tasks or implement particular abstract datatypes. Computer system/server 12 may be practiced in distributed cloudcomputing environments where tasks are performed by remote processingdevices that are linked through a communications network. In adistributed cloud computing environment, program modules may be locatedin both local and remote computer system storage media including memorystorage devices.

As shown in FIG. 1 , computer system/server 12 in cloud computing node10 is shown in the form of a general-purpose computing device. Thecomponents of computer system/server 12 may include, but are not limitedto, one or more processors or processing units 16, a system memory 28,and a bus 18 that couples various system components including systemmemory 28 to processor 16.

Bus 18 represents one or more of any of several types of bus structures,including a memory bus or memory controller, a peripheral bus, anaccelerated graphics port, and a processor or local bus using any of avariety of bus architectures. By way of example, and not limitation,such architectures include Industry Standard Architecture (ISA) bus,Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, VideoElectronics Standards Association (VESA) local bus, and PeripheralComponent Interconnects (PCI) bus.

Computer system/server 12 typically includes a variety of computersystem readable media. Such media may be any available media that isaccessible by computer system/server 12, and it includes both volatileand non-volatile media, removable and non-removable media.

System memory 28 can include computer system readable media in the formof volatile memory, such as random access memory (RAM) 30 and/or cachememory 32. Computer system/server 12 may further include otherremovable/non-removable, volatile/non-volatile computer system storagemedia. By way of example only, storage system 34 can be provided forreading from and writing to a non-removable, non-volatile magnetic media(not shown and typically called a “hard drive”). Although not shown, amagnetic disk drive for reading from and writing to a removable,non-volatile magnetic disk (e.g., a “floppy disk”), and an optical diskdrive for reading from or writing to a removable, non-volatile opticaldisk such as a CD-ROM, DVD-ROM or other optical media can be provided.In such instances, each can be connected to bus 18 by one or more datamedia interfaces. As will be further depicted and described below,memory 28 may include at least one program product having a set (e.g.,at least one) of program modules that are configured to carry out thefunctions of embodiments of the invention.

Program/utility 40, having a set (at least one) of program modules 42,may be stored in memory 28 by way of example, and not limitation, aswell as an operating system, one or more application programs, otherprogram modules, and program data. Each of the operating system, one ormore application programs, other program modules, and program data orsome combination thereof, may include an implementation of a networkingenvironment. Program modules 42 generally carry out the functions and/ormethodologies of embodiments of the invention as described herein.

Computer system/server 12 may also communicate with one or more externaldevices 14 such as a keyboard, a pointing device, a display 24, etc.;one or more devices that enable a user to interact with computersystem/server 12; and/or any devices (e.g., network card, modem, etc.)that enable computer system/server 12 to communicate with one or moreother computing devices. Such communication can occur via Input/Output(I/O) interfaces 22. Still yet, computer system/server 12 cancommunicate with one or more networks such as a local area network(LAN), a general wide area network (WAN), and/or a public network (e.g.,the Internet) via network adapter 20. As depicted, network adapter 20communicates with the other components of computer system/server 12 viabus 18. It should be understood that although not shown, other hardwareand/or software components could be used in conjunction with computersystem/server 12. Examples, include, but are not limited to: microcode,device drivers, redundant processing units, external disk drive arrays,RAID systems, tape drives, and data archival storage systems, etc.

Referring now to FIG. 2 , illustrative cloud computing environment 50 isdepicted. As shown, cloud computing environment 50 includes one or morecloud computing nodes 10 with which local computing devices used bycloud consumers, such as, for example, personal digital assistant (PDA)or cellular telephone 54A, desktop computer 54B, laptop computer 54C,and/or automobile computer system 54N may communicate. Nodes 10 maycommunicate with one another. They may be grouped (not shown) physicallyor virtually, in one or more networks, such as Private, Community,Public, or Hybrid clouds as described hereinabove, or a combinationthereof. This allows cloud computing environment 50 to offerinfrastructure, platforms and/or software as services for which a cloudconsumer does not need to maintain resources on a local computingdevice. It is understood that the types of computing devices 54A-N shownin FIG. 2 are intended to be illustrative only and that computing nodes10 and cloud computing environment 50 can communicate with any type ofcomputerized device over any type of network and/or network addressableconnection (e.g., using a web browser).

Referring now to FIG. 3 , a set of functional abstraction layersprovided by cloud computing environment 50 (FIG. 2 ) is shown. It shouldbe understood in advance that the components, layers, and functionsshown in FIG. 3 are intended to be illustrative only and embodiments ofthe invention are not limited thereto. As depicted, the following layersand corresponding functions are provided:

Hardware and software layer 60 includes hardware and softwarecomponents. Examples of hardware components include: mainframes 61; RISC(Reduced Instruction Set Computer) architecture based servers 62;servers 63; blade servers 64; storage devices 65; and networks andnetworking components 66. In some embodiments, software componentsinclude network application server software 67 and database software 68.

Virtualization layer 70 provides an abstraction layer from which thefollowing examples of virtual entities may be provided: virtual servers71; virtual storage 72; virtual networks 73, including virtual privatenetworks; virtual applications and operating systems 74; and virtualclients 75.

In one example, management layer 80 may provide the functions describedbelow.

Resource provisioning 81 provides dynamic procurement of computingresources and other resources that are utilized to perform tasks withinthe cloud computing environment. Metering and Pricing 82 provide costtracking as resources are utilized within the cloud computingenvironment, and billing or invoicing for consumption of theseresources. In one example, these resources may include applicationsoftware licenses. Security provides identity verification for cloudconsumers and tasks, as well as protection for data and other resources.User portal 83 provides access to the cloud computing environment forconsumers and system administrators. Service level management 84provides cloud computing resource allocation and management such thatrequired service levels are met. Service Level Agreement (SLA) planningand fulfillment 85 provide pre-arrangement for, and procurement of,cloud computing resources for which a future requirement is anticipatedin accordance with an SLA.

Workloads layer 90 provides examples of functionality for which thecloud computing environment may be utilized. Examples of workloads andfunctions which may be provided from this layer include: mapping andnavigation 91; software development and lifecycle management 92; virtualclassroom education delivery 93; data analytics processing 94;transaction processing and videoconferencing security 96.

Implementations of the invention may include a computer system/server 12of FIG. 1 in which one or more of the program modules 42 are configuredto perform (or cause the computer system/server 12 to perform) one ofmore functions of the videoconferencing security 96 of FIG. 3 . Forexample, the one or more of the program modules 42 may be configured to:determine a level of tolerated risk for a videoconference between apresenter and an attendee; obtain sensor data from at least one sensorat a location where a user device of the attendee displays thevideoconference; generate a current risk score based on the sensor data,wherein the current risk score is a probability that another person isin the location where the user device of the attendee displays thevideoconference; determine the current risk score exceeds the level oftolerated risk; and in response to the determining the current riskscore exceeds the level of tolerated risk, present an alert to thepresenter of the videoconference.

FIG. 4 shows a block diagram of an exemplary environment in accordancewith aspects of the invention. In embodiments, the environment includesplural user devices 405, 407 and a videoconference server 410 connectedto a network 415. The network 415 comprises one or more communicationnetworks such as one or more of a LAN, WAN, and the Internet. Each ofthe user devices 405, 407 (also called an endpoint device) comprises acomputing device such as a smartphone, tablet computer, laptop computer,desktop computer, etc., and may comprise one or more elements of thecomputer system 12 of FIG. 1 . In embodiments, each of the user devices405, 407 comprises a conference client application 420, which maycomprise a software application such as a program/utility 40 of FIG. 1 .

In embodiments, the videoconference server 410 comprises one or morecomputing servers each comprising one or more elements of computersystem 12 of FIG. 1 . In other embodiments, the videoconference server410 comprises one or more virtual machines or one or more containersrunning on one or more computing servers. In a cloud embodiment, thenetwork 415 comprises the cloud computing environment 50 of FIG. 2 , thevideoconference server 410 comprises one or more nodes 10, and the userdevices 405, 407 each comprise one of computing devices 54A-N.

In embodiments, the videoconference server 410 comprises a conferenceapplication 425 which may comprise a software application such as aprogram/utility 40 of FIG. 1 . In embodiments, the videoconferenceserver 410 comprises a security module 430, which may comprise one ormore program modules such as program modules 42 described with respectto FIG. 1 . In one example, the security module 430 comprises a plug-in,add-on, or extension of the conference application 425. Thevideoconference server 410 may include additional or fewer programs andmodules than those shown in FIG. 4 . In embodiments, separate programsor modules may be integrated into a single program or module.Additionally, or alternatively, a single program or module may beimplemented as multiple programs or modules. Moreover, the quantity ofdevices and/or networks in the environment is not limited to what isshown in FIG. 4 . In practice, the environment may include additionaldevices and/or networks; fewer devices and/or networks; differentdevices and/or networks; or differently arranged devices and/or networksthan illustrated in FIG. 4 .

In embodiments, the conference application 425 comprises avideoconferencing application that communicates with respectiveinstances of the conference client application 420 on the user devices405, 407 to provide videoconferencing services and functionality to theusers of the user devices 405, 407. For example, the conferenceapplication 425 may receive audio and video signals from each of theuser devices 405, 407 and generate a conference audio/video stream foroutput at each of the user devices 405, 407 so that the users of theuser devices 405, 407 can participate in real-time videoconferencing. Inembodiments, the conference application 425 is configured to permit auser of one of the user devices (e.g., 405) to share their screen withusers of the other user devices (e.g., 407) during the real-timevideoconferencing. For example, a first user may opt to share theirscreen showing a word-processing document, and the other users in thevideoconference can see the screenshared portion of the word-processingdocument in a user interface of the conference client application 420 ontheir respective devices.

In embodiments, the conference application 425 is configured to permit auser of one of the user devices (e.g., 405) to be a presenter of thevideoconference and another one of the user devices (e.g., 407) to be anattendee of the videoconference. For simplicity, only two user devices405, 407 are shown in FIG. 4 ; however, there may be any number of userdevices connected to the network 415 and associated with avideoconference in which one user is the presenter and all the otherusers are attendees. In embodiments, the conference application 425 andconference client application 420 are configured so that the presenterhas access to certain videoconference controls that the attendee doesnot, as is common in the art. For example, the system may permit thepresenter to provide input to perform actions such as allow attendees tojoin the videoconference (e.g., from a waiting room), disconnectattendees from the videoconference, turn off attendee audio feeds in thevideoconference, turn off attendee video feeds in the videoconference,etc.

With continued reference to FIG. 4 , in embodiments there is at leastone sensor 435 at a location 440 associated with the user device 407(e.g., the attendee user device in this example). The location 440comprises a real-world, physical location such as a room or cubicle, forexample. In embodiments, the sensor 435 comprises one or more sensorsthat collect data that can be used to detect when another person is inthe location 440 with the attendee. For example, and without limitation,the sensor 435 may comprise one or more of: one or more video cameras,one or more ultrasonic sensors, one or more infrared sensors, one ormore light detection and ranging (LIDAR) sensors, one or more Li-Fisensors, one or more microphones, and one or more carbon contentdetection sensors. In one example, the sensors 435 comprise IoT sensorsthat are communicatively connected to the network 415 and that publishinformation to the network 415 for purposes that are unrelated tovideoconferencing. In this example, the security module 430 leveragesdata generated by the IoT sensors for the auxiliary purpose of providingenhanced security to a videoconference hosted by the videoconferenceserver 410. In another example, one or more of the sensors 435 may notbe connected to the network 415 and may instead be accessed by the userdevice 407 communicating with the sensor. In this example, the userdevice 407 obtains data from the sensor and communicates the data to thevideoconference server 410 via the network 415.

According to aspects of the invention, the security module 430 isconfigured to receive data from the sensors 435, detect when a personother than the attendee is in the location 440 based on the data fromthe sensors 435, and generate an alert to one or both the user devices405, 407 based on the detecting the other person in the location 440.

In embodiments, the security module 430 is configured to determine whenconfidential data is displayed in the videoconference, and to generatethe alert only when confidential data is being displayed and a personother than the attendee is in the location 440. In one example, thesecurity module 430 determines when confidential data is being displayedin the videoconference based on user input (e.g., from the presenterusing device 405). In another example, the security module 430automatically determines when confidential data is being displayed inthe videoconference by using an artificial intelligence component, suchas natural language processing, object recognition in images, etc.

FIG. 5 shows an exemplary use case of the environment of FIG. 4 inaccordance with aspects of the invention. In the example shown in FIG. 5, an attendee 507 uses their user device 407 to participate in avideoconference hosted by the videoconference server 410 and presentedby a presenter using the user device 405. In the example shown in FIG. 5, the attendee 407 is in a location 440 (e.g., a conference room) thatis equipped with one or more sensors 435. In the example shown in FIG. 5, another person 509 is also in the location 440 and this other person509 is not part of the videoconference. In the example shown in FIG. 5 ,the other person 509 can see 511 the display of the attendee's userdevice 407 that is showing the video feed of the videoconference. Inthis example, if confidential data is included in the video feed of thevideoconference, then there is the likelihood of a data breach becausethe other person 509 can see the confidential data as it is being shownon the attendee's user device 407. Implementations of the inventionaddress this problem by detecting when confidential data is shown in thevideoconference, detecting when there is another person in a location ofan attendee of the videoconference, and generating an alert when bothconditions are satisfied concurrently. In the example shown in FIG. 5 ,the alert can take the form of a visual indicator 513 (selected from oneof plural different visual indictors) displayed in the videoconferenceinterface 515 of the user device 405 of the presenter.

With continued reference to FIGS. 4 and 5 , in embodiments the securitymodule 430 permits the presenter to define confidentiality requirementsfor a videoconference prior to permitting attendees to connect to thevideo conference. This defining of confidentiality requirements may beperformed by the presenter in the videoconference interface on thepresenter's user device (e.g., 405). One example of a confidentialityrequirement is a set of prerequisites that attendees must adhere toduring the videoconference. The prerequisites may include, for example:attendees should be alone in the field of view of the display of theiruser device (e.g., 407) during the videoconference; attendees should notuse their user device to screenshot or record any content of thevideoconference; attendees should not use another camera device to takea picture of the display of their user device during thevideoconference; attendees should not save content of thevideoconference to their user device; attendees should use earbuds orheadphones to listen to the videoconference; and attendees shouldperform other presenter-defined activities on their user device duringthe videoconference.

Another example of a confidentiality requirement is the presenterproviding user input to define certain portions of the content asconfidential data. This may include, for example, tagging certainportions of a document (e.g., passages, paragraphs, pages, slides, etc.)as being confidential. Alternatively, to the presenter manually definingthe confidential data, the security module 430 may automaticallyidentify confidential data in the content of the videoconference. Forexample, the security module 430 may use artificial intelligence toautomatically identify confidential data in the content of thevideoconference. The artificial intelligence may include, for example, atext-based sensitivity technique or a video-subscript-based machinelearning technique that identifies whether content contains confidentialdata. Additionally, or alternatively, the artificial intelligence mayinclude natural language processing and keyword detection. For example,using keyword detection, the security module 430 may detect the word“confidential” on a slide of a document and may tag that slide ascontaining confidential data. In another example, using natural languageprocessing the security module 430 may detect the phrase “this entiredocument is confidential” on one page of a multipage document and, basedon this, may tag all pages of the document as confidential. Theseexamples are non-limiting, and other techniques may be used toautomatically identify confidential data in the content of thevideoconference.

Another example of a confidentiality requirement is the presenterproviding user input to define a level of tolerated risk for thevideoconference. In one example, the level of tolerated risk is anumerical value that the presenter can input in a form field or by usinga dial or slider in the videoconference interface on the presenter'suser device (e.g., 405). In another example, the level of tolerated riskis one of a predefined set of levels such as low, medium, and high. Inthis example, each one of low, medium, and high has a differentnumerical value associated with it, and the numerical value of the oneselected by the presenter (e.g., low, medium, and high) is set as thelevel of tolerated risk. As described later with respect to step 625 ofFIG. 6 , the numerical value of the level of tolerated risk may be setas a second threshold for determining which one of plural visualindicators to display to the presenter, and a first threshold may bedetermined as a function of the second threshold.

With continued reference to FIGS. 4 and 5 , in embodiments the securitymodule 430 identifies the sensors 435 in the location 440. Inembodiments, the security module 430 prompts the conference clientapplication 420 on the attendee user device 407 to search for sensors435 in the location 440. For example, in response to the prompt from thesecurity module 430, the conference client application 420 on theattendee user device 407 may use a discovery process to locate sensors435 and may use an API specific to each sensor 435 to connect to thesensor. In embodiments, the security module 430 determines whether theattendee user device 407 has permission to access the sensors 435, suchthat at runtime the security module 430 can selectively enable anddisable collection of data from the sensors for the analysis describedherein.

With continued reference to FIGS. 4 and 5 , in embodiments the securitymodule 430 identifies capabilities of the attendee user device 407. Inembodiments, the security module 430 prompts the attendee user device407 to identify whether any sensors are available in the attendee userdevice 407 itself. For example, many endpoint devices, such as a laptop,tablet, or smartphone, include one or more of a camera, infrared sensor,and ultrasonic sensor. In embodiments, the security module 430 mayobtain data from such sensors integrated in the attendee user device 407and may use the data from these sensors for the analysis describedherein. In one example, the security module 430 obtains data from IoTsensors that are separate from the attendee user device 407, obtainsdata from sensors integrated in the attendee user device 407, and usesthe data from both types of sensors for the analysis described herein.In embodiments, the security module 430 prompts the attendee user device407 to indicate whether the attendee user device 407 includes abackground recording and/or screenshot function, and to enable thesecurity module 430 to disable these functions on the attendee userdevice 407 during the videoconference.

With continued reference to FIGS. 4 and 5 , in embodiments the securitymodule 430 obtains sensor data from the sensors 435. In embodiments, thesecurity module 430 prompts the user device 407 to obtain sensor datafrom the sensors 435 when confidential data is presented in thevideoconference. In some implementations, the security module 430 doesnot obtain sensor data during times when no confidential data ispresented in the videoconference, thus reducing the usage of computingresources.

In embodiments, when plural sensors are available (e.g., one or more IoTsensors and/or one or more sensors of the user device 407), the securitymodule 430 selects a subset of the plural sensors and obtains sensordata from only the selected subset. In embodiments, the security module430 selects the subset based on determining which of the sensors is mostrelevant in the current situation. The relative relevancy of the sensordata may be determined based on a quality of the sensor data, forexample based on confidence levels of predictions made using the sensordata. In embodiments, the security module 430 disables the function ofcollecting sensor data from sensors that are not in the selected subset,thus reducing the usage of computing resources.

With continued reference to FIGS. 4 and 5 , in embodiments the securitymodule 430 uses the obtained sensor data to generate a current riskscore associated with the user device 407. In implementations, thecurrent risk score is a probability that another person is in thelocation 400 where the attendee user device 407 displays thevideoconference. In embodiments, the current risk score is generatedusing a machine learning model that receives the sensor data as inputand that outputs the probability that another person is in the locationwhere the user device of the attendee displays the videoconference.Different machine learning models may be trained with different trainingdata and used for different types of sensors. As but one example, aconvolutional neural network may be trained using training data that isspecific to camera data, and the trained convolutional neural networkmay be used in real time with data from a camera included in the sensors435 to generate a probability that another person is in the location 400where the attendee user device 407 displays the videoconference. Whendata from a single one of the sensors 435 is used, the current riskscore may be set as the probability derived using the data of that onesensor. When data from plural ones of the sensors 435 is used, thecurrent risk score may be determined as a function of the pluralprobabilities derived using the data of the plural sensors. In oneexample, the function is a non-weighted average of the pluralprobabilities. In another example, the function is a weighted average ofthe plural probabilities.

In one exemplary implementation, the sensor 435 comprises a camera, thesensor data is image data of the camera that captures an expression ofthe attendee during the videoconference, and the risk score is generatedbased on the expression of the attendee. In this implementation, thesecurity module 430 uses machine learning to learn facial expressions ofthe attendee that indicate another person is on the room. In thismanner, the security module 430 may use the trained machine learningmodel in real time, with the attendee's facial expressions during thevideoconference, to predict whether another person is in the room withthe attendee.

With continued reference to FIGS. 4 and 5 , in embodiments, in responseto determining the current risk score exceeds the level of toleratedrisk, the security module 430 presents an alert to the presenter of thevideoconference. In embodiments, based on the collected sensor data, thesecurity module 430 identifies whether an unauthorized person is in thelocation 440 and then presents an alert to the presenter. Upon receivingthe alert, the presenter may perform an action in the videoconference,such as: stop presenting until the anomaly is resolved; warn theattendee of the anomaly; and send message to attendee indicating thatthe videoconference will continue only after the attendee resolves theidentified anomaly.

With continued reference to FIGS. 4 and 5 , in embodiments, in responseto determining the current risk score exceeds the level of toleratedrisk, the security module 430 may also present an alert to the attendee.In response, the attendee may take action such as: change the angle oftheir user device 407 so that the unauthorize person cannot see thedisplay of the user device 407; and move to another location.

In additional embodiments, the security module 430 may notify thepresenter prior to the videoconference that the attendee's user device407 does not have a certain capability. Upon receiving this information,the presenter might take action such as ask the attendee to add thecapability to their user device 407 before beginning thevideoconference.

In additional embodiments, the security module 430 may notify thepresenter prior to the videoconference that the attendee is currently ina situation (e.g., travel) in which the attendee cannot satisfy one ormore of the prerequisites. Upon receiving this information, thepresenter might take action such as reschedule the videoconference to alater time when the attendee will be able to satisfy all of theprerequisites.

FIG. 6 shows a flowchart of an exemplary method in accordance withaspects of the invention. Steps of the method may be carried out in theenvironment of FIG. 4 and are described with reference to elementsdepicted in FIG. 4 .

At step 605, the system determines confidentiality requirements of avideoconference that is presented by a presenter using user device 405and attended by an attendee using user device 407. In embodiments, thesecurity module 430 determines the confidentiality requirements of avideoconference based on at least one of user input and automatedtechniques. In embodiments, the user input comprises the videoconferencepresenter defining confidentiality requirements via theirvideoconference interface. This may include, for example, taggingcertain portions of a document (e.g., passages, paragraphs, pages,slides, etc.) as being confidential. In embodiments, the automatedtechniques comprise conventional or later-developed automated techniquesfor identifying confidential data in a document. This may include, forexample, natural language processing and keyword detection. Theconfidentiality requirements may also include a level of tolerated riskfor the videoconference defined by the presenter.

At step 610, the system establishes a respective sensor cohort for eachattendee of the videoconference. In embodiments, the client conferenceapplication 420 on the user device 407 discoveries and connects tosensors 435 in the location 440 of the user device 407. The discoveryand connection may be performed using application programming interfaces(APIs) for each of the sensors. The senor cohort may additionally oralternatively include one or more sensors that are integrated with theuser device 407. In embodiments, step 610 includes reporting sensor datafrom the sensor cohort to the security module 430.

At step 615, the system detects the presence of another person in thelocation with the attendee and user device 407. In embodiments, thesecurity module 430 analyzes the sensor cohort data to derive a scoredprobability of another human presence for each attendee. In embodiments,for each attendee of the videoconference, the security module 430receives data from the sensors 435 in real time and uses the data todetermine whether another person is in the same location as theattendee. The presence detection may be performed by a presencedetection module that is part of or communicates with the securitymodule 430. The presence detection may be performed using one or moreof: object detection (e.g., using a convolutional neural network) usingdata from a camera; motion sensing using data from an infrared sensor;light fidelity analysis using data from a Li-Fi sensor; ultrasonic humanpresence detection using data from an ultrasonic sensor; carbon contentdetection using data from a carbon content detection sensor; and LIDARdepth scan using data from a LIDAR sensor. In embodiments, the securitymodule 430 determines a confidence score of the presence detection foreach sensor used in the making the presence detection, wherein theconfidence score represents a probability that another person is in thelocation with the attendee.

At step 620, the system generates an anomaly score (also called acurrent risk score) for each attendee. In embodiments, the securitymodule 430 generates the anomaly score based on a confidence score(s) ofthe presence detection. In embodiments, when only one sensor 435 is usedto make the presence detection at step 615, then the anomaly score isthe confidence score of the presence detection derived from the data ofthat one sensor. In embodiments, when plural sensors 435 are used tomake the presence detection at step 615, then the anomaly score is afunction of the respective confidence scores of the presence detectionsderived from the data of the plural sensors. In one example, thefunction is a non-weighted average of the confidence scores of thepresence detections of the plural sensors. In another example, thefunction is a weighted average of the confidence scores of the presencedetections of the plural sensors, where the weights are configurable insettings of the security module 430. The generating the anomaly scoremay be performed by an anomaly scoring module that is part of orcommunicates with the security module 430. In embodiments, the anomalyscoring module reports the scoring for the videoconference.

At step 625, the system presents an alert to the presenter of thevideoconference based on the anomaly score from step 620. Inembodiments, the system augments the videoconference presenter's viewwith a visualization of a probability that each attendee is within theconfines of the defined conference confidentiality requirements. Inembodiments, the security module 430 causes the conference clientapplication 420 to display one of plural predefined visual indicationsin the videoconference interface of the presenter's user device 405based in the anomaly score from step 620. In one example, the pluralpredefined icons include a first icon, a second icon, and a third icon.In this example, the security module 430 causes the conference clientapplication 420 to display the first icon when the anomaly score is lessthan a first threshold, to display the second icon when the anomalyscore is between the first threshold and a second threshold, and todisplay the third icon when the anomaly score is greater than the secondthreshold. In this example, the first icon may be green and signify therisk level is low, the second icon may be yellow and signify the risklevel is medium, and the third icon may be red and signify the risklevel is high. The presenter may perform an action in thevideoconference based on which icon is displayed in theirvideoconference interface.

Still referring to step 625, in one example the second threshold is setas the numerical value of the level of tolerated risk. In this example,the first threshold may be computed based on a predefined function, suchas half the second threshold.

FIG. 7 shows a flowchart of an exemplary method in accordance withaspects of the present invention. Steps of the method may be carried outin the environment of FIG. 4 and are described with reference toelements depicted in FIG. 4 .

At step 705, the system determines a level of tolerated risk for avideoconference between a presenter and an attendee. At step 710, thesystem obtains sensor data from at least one sensor at a location wherea user device of the attendee displays the videoconference. At step 715,the system generates a current risk score based on the sensor data. Atstep 720, the system determines the current risk score exceeds the levelof tolerated risk. At step 725, in response to the determining thecurrent risk score exceeds the level of tolerated risk at step 720, thesystem presents an alert to the presenter of the videoconference.

In embodiments, the alert comprises a visual indicator shown in aninterface of the videoconference. In embodiments, the alert comprisesone of plural visual indicators shown in an interface of thevideoconference, the plural visual indicators comprising: a first visualindicator having a first color and signifying a first level of concern;a second visual indicator having a second color and signifying a secondlevel of concern; and a third visual indicator having a third color andsignifying a third level of concern, wherein the first color, the secondcolor, and the third color are all different from one another.

In embodiments, a service provider could offer to perform the processesdescribed herein. In this case, the service provider can create,maintain, deploy, support, etc., the computer infrastructure thatperforms the process steps of the invention for one or more customers.These customers may be, for example, a business that providesvideoconferencing. In return, the service provider can receive paymentfrom the customer(s) under a subscription and/or fee agreement and/orthe service provider can receive payment from the sale of advertisingcontent to one or more third parties.

In still additional embodiments, the invention provides acomputer-implemented method, via a network. In this case, a computerinfrastructure, such as computer system/server 12 (FIG. 1 ), can beprovided and one or more systems for performing the processes of theinvention can be obtained (e.g., created, purchased, used, modified,etc.) and deployed to the computer infrastructure. To this extent, thedeployment of a system can comprise one or more of: (1) installingprogram code on a computing device, such as computer system/server 12(as shown in FIG. 1 ), from a computer-readable medium; (2) adding oneor more computing devices to the computer infrastructure; and (3)incorporating and/or modifying one or more existing systems of thecomputer infrastructure to enable the computer infrastructure to performthe processes of the invention.

The descriptions of the various embodiments of the present inventionhave been presented for purposes of illustration, but are not intendedto be exhaustive or limited to the embodiments disclosed. Manymodifications and variations will be apparent to those of ordinary skillin the art without departing from the scope and spirit of the describedembodiments. The terminology used herein was chosen to best explain theprinciples of the embodiments, the practical application or technicalimprovement over technologies found in the marketplace, or to enableothers of ordinary skill in the art to understand the embodimentsdisclosed herein.

What is claimed is:
 1. A method, comprising: determining, by avideoconference server, a level of tolerated risk for a videoconferencebetween a presenter and an attendee; obtaining, by the videoconferenceserver, sensor data from at least one sensor at a location where a userdevice of the attendee displays the videoconference; generating, by thevideoconference server, a current risk score based on the sensor data;determining, by the videoconference server, the current risk scoreexceeds the level of tolerated risk; and presenting, by thevideoconference server and in response to the determining the currentrisk score exceeds the level of tolerated risk, an alert to thepresenter of the videoconference.
 2. The method of claim 1, furthercomprising identifying confidential data in a portion of thevideoconference, wherein the videoconference server obtains the sensordata, generates the current risk score, determines the current riskscore exceeds the level of tolerated risk, and presents the alert basedon the confidential data being displayed in the videoconference.
 3. Themethod of claim 2, wherein the videoconference server obtains the sensordata, generates the current risk score, determines the current riskscore exceeds the level of tolerated risk, and presents the alert onlyat times when the confidential data is displayed in the videoconference.4. The method of claim 2, wherein the videoconference server identifiesthe confidential data based on user input that defines the confidentialdata.
 5. The method of claim 2, wherein the videoconference serveridentifies the confidential data automatically using artificialintelligence.
 6. The method of claim 1, wherein the at least one sensorcomprises one or more selected from the group consisting of: a camera;an ultrasonic sensor; an infrared sensor; a light detection and ranging(LIDAR) sensor; a Li-Fi sensor; a microphone; and a carbon contentdetection sensor.
 7. The method of claim 6, wherein the at least onesensor is integrated in the user device of the attendee.
 8. The methodof claim 6, wherein the at least one sensor is separate from the userdevice of the attendee.
 9. The method of claim 8, wherein: thevideoconference server causes the user device of the attendee to connectto the at least one sensor; and the videoconference server receives thesensor data from the at least one sensor via the user device of theattendee.
 10. The method of claim 1, wherein the current risk score is aprobability that another person is in the location where the user deviceof the attendee displays the videoconference.
 11. The method of claim10, wherein: the at least one sensor comprises a camera; the sensor datais image data of the camera that captures an expression of the attendeeduring the videoconference; and the risk score is generated based on theexpression of the attendee.
 12. A computer program product comprisingone or more computer readable storage media having program instructionscollectively stored on the one or more computer readable storage media,the program instructions executable to cause a videoconference serverto: determine a level of tolerated risk for a videoconference between apresenter and an attendee; obtain sensor data from at least one sensorat a location where a user device of the attendee displays thevideoconference; generate a current risk score based on the sensor data,wherein the current risk score is a probability that another person isin the location where the user device of the attendee displays thevideoconference; determine the current risk score exceeds the level oftolerated risk; and in response to the determining the current riskscore exceeds the level of tolerated risk, present an alert to thepresenter of the videoconference.
 13. The computer program product ofclaim 12, wherein the alert comprises a visual indicator shown in aninterface of the videoconference.
 14. The computer program product ofclaim 12, wherein the alert comprises one of plural visual indicatorsshown in an interface of the videoconference, the plural visualindicators comprising: a first visual indicator having a first color andsignifying a first level of concern; a second visual indicator having asecond color and signifying a second level of concern; and a thirdvisual indicator having a third color and signifying a third level ofconcern, wherein the first color, the second color, and the third colorare all different from one another.
 15. The computer program product ofclaim 12, wherein the current risk score is generated using a machinelearning model that receives the sensor data as input and that outputsthe probability that another person is in the location where the userdevice of the attendee displays the videoconference.
 16. The computerprogram product of claim 12, wherein the program instructions areexecutable to cause the videoconference server to instruct the userdevice of the attendee to disable video recording and screenshotfunctions during the videoconference.
 17. A system comprising: aprocessor, a computer readable memory, one or more computer readablestorage media, and program instructions collectively stored on the oneor more computer readable storage media, the program instructionsexecutable to: determine a level of tolerated risk for a videoconferencebetween a presenter and an attendee; obtain sensor data from at leastone sensor at a location where a user device of the attendee displaysthe videoconference; generate a current risk score based on the sensordata, wherein the current risk score is a probability that anotherperson is in the location where the user device of the attendee displaysthe videoconference; determine the current risk score exceeds the levelof tolerated risk; and in response to the determining the current riskscore exceeds the level of tolerated risk concurrently with confidentialdata being displayed in the videoconference, present an alert to thepresenter of the videoconference.
 18. The system of claim 17, whereinthe location comprises a room and the user device of the attendee is inthe room.
 19. The system of claim 17, wherein the alert comprises avisual indicator shown in an interface of the videoconference.
 20. Thesystem of claim 17, wherein the alert comprises one of plural visualindicators shown in an interface of the videoconference, the pluralvisual indicators comprising: a first visual indicator having a firstcolor and signifying a first level of concern; a second visual indicatorhaving a second color and signifying a second level of concern; and athird visual indicator having a third color and signifying a third levelof concern, wherein the first color, the second color, and the thirdcolor are all different from one another.